Triple

T13578055
Position Surface form Disambiguated ID Type / Status
Subject John Copley, 1st Baron Lyndhurst E324338 entity
Predicate spouse P13 FINISHED
Object Sarah Brunsden E335667 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sarah Brunsden | Statement: [John Copley, 1st Baron Lyndhurst, spouse, Sarah Brunsden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarah Brunsden
Context triple: [John Copley, 1st Baron Lyndhurst, spouse, Sarah Brunsden]
  • A. Sarah Brunsden chosen
    Sarah Brunsden was the wife of Sir John Copley, a British legal figure who served as Lord Chancellor in the early 19th century.
  • B. Sarah Troughton
    Sarah Troughton is a British public figure and member of the extended royal family who serves as the ceremonial representative of the Crown in Wiltshire.
  • C. Sarah Barnard
    Sarah Barnard is a relatively obscure individual for whom no widely known public information or distinguishing background is readily available.
  • D. Sarah Barnard
    Sarah Barnard was the wife of renowned English scientist Michael Faraday, providing personal support throughout his career in 19th-century London.
  • E. Susannah York
    Susannah York was an acclaimed English actress known for her versatile performances in film, television, and theatre during the 1960s and 1970s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb02de1988190af2d473973ecd529 completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d6fde508190865a8e3e391fdf5e completed May 8, 2026, 4:58 a.m.
Created at: April 9, 2026, 9:48 p.m.